CN-122025700-A - Control method, system, medium and equipment of flow battery thermal management module unit

CN122025700ACN 122025700 ACN122025700 ACN 122025700ACN-122025700-A

Abstract

The invention belongs to the field of flow batteries, and particularly relates to a control method, a system, a medium and equipment of a flow battery thermal management module unit, wherein the method comprises the steps of predicting a power grid dispatching curve based on a day-ahead dispatching model to obtain a waste wind waste light time and waste electric power, and further determining a waste electric period, a non-waste electric period and available waste wind waste electric energy; the method comprises the steps of calculating temperatures T 1 and T 2 through an economic operation model algorithm, and controlling by adopting an economic operation mode based on a power discarding period, a non-power discarding period, T 1 and T 2 , wherein the method comprises the steps of utilizing wind discarding photoelectric energy to conduct heat management power supply in the power discarding period, controlling a heat management module unit to conduct heating or refrigeration to enable the temperature of an energy storage system to be maintained between temperatures T 1 and T max , and utilizing electric network electric energy to conduct heat management power supply in the non-power discarding period, and controlling the heat management module unit to conduct heating or refrigeration to enable the temperature of the energy storage system to be maintained between temperatures T 2 and T max . The invention can fully utilize the wind and light discarding electric energy and effectively reduce the operation electricity cost of the thermal management module unit.

Inventors

GUO XIAOYU
YANG RUILIN
ZHANG HANGRUI
ZHENG XIN
ZHOU JIE
ZHANG RONG
ZHANG JINYI
WANG JIANJUN
GONG ZHEN
YU WEI

Assignees

北京和瑞储能科技有限公司

Dates

Publication Date: 20260512
Application Date: 20241111

Claims (10)

1. A method for controlling a flow battery thermal management module assembly, the method comprising: Predicting a power grid dispatching curve based on a day-ahead dispatching model to obtain a waste wind waste light time and waste electric power, determining a waste electric period and a non-waste electric period according to the waste wind waste light time, and determining available waste wind waste electric energy according to the waste wind waste light time and the waste electric power; The temperature T 1 and the temperature T 2 are obtained through iterative optimization calculation of an economic operation model algorithm, the temperature T 1 is the temperature capable of maintaining the high-efficiency operation of the flow battery energy storage system, the temperature T 2 is the temperature capable of maintaining the normal operation of the flow battery energy storage system, and the temperature T 1 is higher than the temperature T 2 ; Based on the power discarding period and the non-power discarding period and the temperatures T 1 and T 2 , an economic operation mode is adopted to control the flow battery thermal management module unit, wherein the economic operation mode comprises: And in the non-power-off period, the electric power of the power grid is used for carrying out heat management and power supply, and the heat management module unit is controlled to heat or refrigerate so as to maintain the temperature of the flow battery energy storage system between the temperature T 2 and the upper limit temperature T max .
2. The method for controlling a thermal management module unit of a flow battery according to claim 1, wherein the obtaining temperatures T 1 and T 2 by iterative optimization calculation of an economic operation model algorithm comprises: And taking the operation economy of the thermal management module unit and the operation efficiency of the direct current side energy storage system as an objective function M, and solving the optimal solution of the temperature T 1 and the temperature T 2 by utilizing a genetic algorithm based on the objective function M.
3. The method for controlling a thermal management module unit of a flow battery according to claim 2, wherein the objective function M is an operational efficiency of a thermal management module unit and a dc side energy storage system coupled with operational economy, and the method comprises: operating economy dimensionless value by using thermal management module unit As a first function, the operation efficiency of the direct-current side energy storage system is dimensionless For the second function, the first function and the second function are converted into the objective function M using a dimensionless weighted sum method.
4. The method for controlling a thermal management module unit of a flow battery according to claim 3, wherein the expression of the objective function M is: Wherein alpha is the running economy weight of the thermal management module unit, and gamma is the running efficiency weight of the direct-current side energy storage system.
5. The method for controlling a thermal management module unit of a flow battery according to claim 3 or 4, wherein the expression of the first function is: Wherein, the C 1j is the electric charge of the thermal management module unit when the temperature of the energy storage system is maintained between the temperature T 1j and the upper limit temperature T max of the system in a natural day, C 2j is the electric charge of the thermal management module unit when the temperature of the energy storage system is maintained between the temperature T 1j and the upper limit temperature T max of the system in a power discarding period and the temperature of the energy storage system is maintained between the temperature T 2j and the upper limit temperature T max of the system in a non-power discarding period according to the control of the economic operation mode; Representing the maximum value of the dimensionless value of the operation economy of the thermal management module unit; The method comprises the steps of representing the minimum value of the dimensionless value of the operation economy of the thermal management module unit, wherein a and b are known positive constants, j represents the value of the temperature T 1 、T 2 of a j group generated randomly, and electricity charge data of the j group thermal management module unit are calculated.
6. The method for controlling a thermal management module unit of a flow battery according to claim 3 or 4, wherein the expression of the second function is: Wherein, the D 1j is the operation efficiency of the energy storage system when the temperature of the energy storage system is maintained between the temperature T 1j and the upper limit temperature T max of the system in a natural day, D 2j is the operation efficiency of the energy storage system when the temperature of the energy storage system is maintained between the temperature T 1j and the upper limit temperature T max of the system in a power-off period and the temperature of the energy storage system is maintained between the temperature T 2j and the upper limit temperature T max of the system in a non-power-off period according to the control of the economic operation mode; representing the maximum value of the dimensionless value of the operation efficiency of the direct-current side energy storage system; the method comprises the steps of representing the minimum value of the dimensionless value of the operation efficiency of the direct-current side energy storage system, wherein a and b are known positive constants, j represents the value of the temperature T 1 、T 2 of a j group generated randomly, and the operation efficiency of the direct-current side energy storage system of the j group is calculated.
7. The method for controlling a thermal management module unit of a flow battery according to claim 3 or 4, wherein the solving the optimal solution of the temperature T 1 and the temperature T 2 based on the objective function M by using a genetic algorithm comprises: a. initializing population parameters including population scale, genetic algebra, mutation percentage and cross percentage; b. Randomly initializing a genetic parameter T 1 、T 2 of each individual, wherein each individual refers to a temperature setting scheme of the flow battery energy storage system; c. Calculating corresponding dimensionless specific values C 1 and C 2 of the operation economy of the thermal management module unit at a group of temperatures T 1 、T 2 through a flow battery system heat balance model; d. Calculating corresponding dimensionless specific values D 1 and D 2 of the operation efficiency of the direct-current side energy storage system at a group of temperatures T 1 、T 2 through a relation model of the temperature of the energy storage system and the operation efficiency of the direct-current side energy storage system; e. Taking the reciprocal 1/M of the objective function M as the fitness of each individual of the current population, calculating the fitness value of each individual of the current population, namely optimizing the value of the objective function, so as to embody the adaptability of the individual, determine the probability that the individual is selected in the population, and ensure the genetic evolution of the population towards the optimal solution; f. Performing selection operation, namely performing selection operation on the individuals according to the fitness values, wherein the lower the fitness value is, the more excellent the individuals are, and the individuals with higher fitness are replaced by the individuals with the lowest fitness; g. performing cross operation, randomly selecting two individuals from the population, and performing exchange combination on the two individuals so as to generate new excellent individuals; h. A mutation operation, namely randomly selecting an individual from a population, and mutating a certain gene parameter of the individual, namely randomly changing the gene parameter of the individual, introducing randomness, and increasing population diversity; i. calculating the fitness value of each individual of the current population again; j. And f, judging whether the maximum iteration times or the minimum fitness of the population meets the minimum limit, if the maximum iteration times or the minimum fitness of the population does not meet the judging condition, returning to the step f, and if the maximum iteration times or the minimum fitness of the population meets the judging condition, selecting an individual with the minimum fitness in the population as an optimal solution, and outputting the temperature T 1 、T 2 .
8. A control system of a flow battery thermal management module assembly for implementing the control method of a flow battery thermal management module assembly according to any one of claims 1-7, the system comprising: The prediction module is used for predicting a power grid dispatching curve based on a day-ahead dispatching model to obtain a waste wind waste light time and waste electric power, determining a waste electric period and a non-waste electric period according to the waste wind waste light time, and determining available waste wind waste electric energy according to the waste wind waste light time and the waste electric power; the calculation module is used for obtaining temperatures T 1 and T 2 through iterative optimization calculation of an economic operation model algorithm; And the economic operation control module is used for controlling the flow battery thermal management module unit by adopting an economic operation mode based on the power discarding time period and the non-power discarding time period and the temperatures T 1 and T 2 .
9. A computer-readable storage medium storing one or more programs, wherein the one or more programs, when executed, implement the method of controlling a flow battery thermal management module assembly of any of claims 1-7.
10. An electronic device comprising a processor, a communication interface, the computer-readable storage medium of claim 9, and a communication bus, wherein the processor, the communication interface, and the computer-readable storage medium communicate with each other over the communication bus; It is characterized in that the method comprises the steps of, The processor is configured to execute a program stored in a computer-readable storage medium.

Description

Control method, system, medium and equipment of flow battery thermal management module unit Technical Field The invention belongs to the technical field of flow batteries, and particularly relates to a control method, a system, a medium and equipment of a flow battery thermal management module unit. Background The interest in low pollution, renewable energy sources continues to increase in various countries. However, renewable energy power generation represented by wind energy and solar power generation is influenced by factors such as time, day and night, seasons and the like, has obvious discontinuous, unstable and uncontrollable unsteady characteristics, needs extra standby capacity to realize dynamic balance, and brings great challenges to the operation of the existing power system. And the large-scale high-efficiency energy storage technology is an important way for solving the problem of unstable power generation of renewable energy sources. The flow battery has the characteristics of low cost, high energy density, good safety, environmental friendliness and the like, and has a good application prospect in the field of large-scale energy storage. In order to further exert the advantages of the flow battery, a certain-scale thermal management module unit needs to be configured, and certain temperature control needs to be met in the charge-discharge operation and standby state so as to ensure that the system operates better and stably. The thermal management power supply of the flow battery energy storage system thermal management module unit mainly comes from electric power of a power grid, the running electricity cost is higher, and the thermal management power supply of the flow battery energy storage system thermal management module unit is not well applied to the flow battery energy storage system thermal management power supply at present. Disclosure of Invention In order to overcome the defects of the background technology, the invention provides a control method of a flow battery thermal management module unit, which can fully utilize the waste wind and waste photoelectric energy and effectively reduce the running electricity cost of the flow battery thermal management module unit. The technical scheme adopted by the invention is that the control method of the flow battery thermal management module unit comprises the following steps: Predicting a power grid dispatching curve based on a day-ahead dispatching model to obtain a waste wind waste light time and waste electric power, determining a waste electric period and a non-waste electric period according to the waste wind waste light time, and determining available waste wind waste electric energy according to the waste wind waste light time and the waste electric power; The temperature T 1 and the temperature T 2 are obtained through iterative optimization calculation of an economic operation model algorithm, the temperature T 1 is the temperature capable of maintaining the high-efficiency operation of the flow battery energy storage system, the temperature T 2 is the temperature capable of maintaining the normal operation of the flow battery energy storage system, and the temperature T 1 is higher than the temperature T 2; Based on the power discarding period and the non-power discarding period and the temperatures T 1 and T 2, an economic operation mode is adopted to control the flow battery thermal management module unit, wherein the economic operation mode comprises: And in the non-power-off period, the electric power of the power grid is used for carrying out heat management and power supply, and the heat management module unit is controlled to heat or refrigerate so as to maintain the temperature of the flow battery energy storage system between the temperature T 2 and the upper limit temperature T max. Further, the method comprises the steps of, The temperature obtaining steps T 1 and T 2 through the iterative optimization calculation of the economic operation model algorithm comprise the following steps: And taking the operation economy of the thermal management module unit and the operation efficiency of the direct current side energy storage system as an objective function M, and solving the optimal solution of the temperature T 1 and the temperature T 2 by utilizing a genetic algorithm based on the objective function M. Further, the method comprises the steps of, The method for using the operation economy of the thermal management module unit to couple the operation efficiency of the direct-current side energy storage system as an objective function M comprises the following steps: operating economy dimensionless value by using thermal management module unit As a first function, the operation efficiency of the direct-current side energy storage system is dimensionlessFor the second function, the first function and the second function are converted into the objective function M using a dimensionless weighted sum method. Further, the m